General and Applied Ecology

A distinction between the pure theory of interconnected systems and its practical, dirty-hands use. General Ecology is the study of universal principles—how energy flows, how populations compete, how systems achieve stability. It's the math and physics of relationships. Applied Ecology is taking those principles and using them to solve real-world problems: restoring a damaged wetland, designing a sustainable city, managing a fishery so it doesn't collapse. It's the difference between knowing the formula for population growth (General) and actually counting the damn fish and dealing with the poachers (Applied).

General and Applied Ecology "My professor can talk for hours about the General Ecology of predator-prey dynamics. Me? I'm doing Applied Ecology, which is trying to keep the squirrels from eating every single tomato in my garden. The theory is elegant; the practice is a warzone."

by Abzugal Nammugal Enkigal February 22, 2026

Social Sciences Applied to AI

The practice of using insights from sociology, anthropology, psychology, and political science to design, understand, and regulate artificial intelligence. It recognizes that AI systems are not neutral math problems but are embedded in human social contexts. This field asks: How will this algorithm affect community dynamics? What social biases is it learning? How does it change power structures? It's the antidote to the naive view that AI is just code, reminding us that every AI is also a social actor.

Example: "They built a great recommendation engine, but without social sciences applied to AI, they accidentally created filter bubbles that radicalized their users."

by Dumu The Void March 11, 2026

Human Sciences Applied to AI

A broader term encompassing all humanities and human-centered disciplines (philosophy, history, linguistics, arts) brought to bear on the development and deployment of artificial intelligence. It goes beyond fixing bias to ask fundamental questions: What does it mean to be human in an age of intelligent machines? How do we preserve dignity, creativity, and meaning? It's the practice of ensuring that as we build smarter machines, we don't build dumber or lesser humans in the process.

Example: "The ethics board was useless until they brought in a philosopher for human sciences applied to AI—he asked questions about personhood that the engineers had never even considered."

by Dumu The Void March 11, 2026

Cognitive Sciences Applied to AI

The practice of using our understanding of the human mind—perception, memory, reasoning, language, and learning—to inspire and improve artificial intelligence. It's the belief that the best way to build a smart machine is to reverse-engineer the only working example we have: the human brain. From neural networks (loosely inspired by neurons) to reinforcement learning (inspired by animal conditioning), this field has been central to AI's development, for better and for worse.

Cognitive Sciences Applied to AI Example: "The chatbot was terrible at conversation until they applied cognitive sciences to AI and taught it to manage turn-taking and context like a real human would."

by Dumu The Void March 11, 2026

Data Science Applied to AI

The engineering and methodological discipline of preparing, cleaning, analyzing, and governing the data that powers artificial intelligence. It recognizes that AI models are only as good as the data they're trained on. This field focuses on the entire data pipeline: sourcing high-quality data, removing bias, ensuring privacy, and managing the massive datasets required to train modern AI. It's the unglamorous but absolutely essential grunt work that makes the magic happen.

Data Science Applied to AI Example: "The model kept failing, and they realized it was a data science applied to AI problem—the training data was full of duplicates and errors they'd never bothered to clean."

by Dumu The Void March 11, 2026

Social Sciences Applied to Social Media

A field of study that uses sociological, anthropological, political, and economic frameworks to analyze how social media platforms shape human behavior, community formation, power dynamics, and cultural production. It examines phenomena like algorithmic governance, influencer economies, digital labor, online identity formation, and the transformation of public discourse. By applying social science tools—ethnography, network analysis, surveys, critical theory—to social media, it moves beyond superficial engagement metrics to understand how platforms mediate social life, reproduce inequality, and create new forms of belonging and exclusion.

Social Sciences Applied to Social Media Example: “Her research applied sociology to TikTok, showing how the algorithm’s preference for controversy pushed creators toward increasingly extreme content—a social science lens revealing the structural drivers of online polarization.”

by Abzugal Nammugal Enkigal March 24, 2026

Human Sciences Applied to Social Media

A complementary field that integrates humanities disciplines—history, philosophy, literature, cultural studies, media studies—into the analysis of social media. It asks questions about meaning, narrative, identity, ethics, and historical continuity. Where social sciences focus on structures and behaviors, human sciences explore the symbolic dimensions: how social media becomes a site for storytelling, selfhood, and cultural memory. It also critically examines the philosophical assumptions built into platform design and the ethical implications of algorithmic mediation.

Example: “Using human sciences applied to social media, he analyzed how Instagram’s aesthetic norms reproduced colonial-era visual hierarchies, turning self-presentation into a politics of visibility and exclusion.”

by Abzugal Nammugal Enkigal March 24, 2026